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Master theses / Diploma theses

Techno-economic assessment of a load-flexible power-to-methanol process under different renewable power supply scenarios (Id 325)

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The Institute of Fluid Dynamics of the Helmholtz-Center Dresden-Rossendorf (HZDR) is engaged in research concerning topics such as modeling and simulation of closely coupled power-to-X systems as well as the analysis of their detailed process behavior and techno-economic performance under fluctuating loads. At the center of the research activities lies the power-to-methanol technology driven by renewable energy based on high temperature electrolysis (SOEC) and the subsequent conversion of H2 together with anthropogenic CO2 into valuable products such as methanol as a climate neutral feedstock or fuel of the future.
Based on an existing system model of a power-to-methanol process as well as a basic techno-economic model, the economic performance of the decentralized production of methanol is to be studied under different scenarios (e.g. grid connection, coupling with PV and wind farms).
The topic includes the following tasks:

  • detailed literature study on the techno-economic assessment (TEA) of power-to-methanol processes as well as the economic characterization of intermittent operating scenarios,
  • gather detailed data of capital expenditures with respect to the purchase costs of all employed components in the system (SOEC, synthesis reactor, compressors, heat exchangers, etc.),
  • further development of the existing techno-economic model within Matlab to assess the methanol production price under fluctuating operation of the decentralized plant in a renewable energy framework,
  • study of the economic performance of a coupling of the power-to-methanol process with a battery storage of suitable size under the premise of a PV or wind farm renewable energy supply.

Department: Experimental Thermal Fluid Dynamics

Contact: Dr. Fogel, Stefan

Requirements

  • students (f/m/d) of industrial engineering, chemical engineering, mechanical engineering, process engineering or any other suitable university education with a bachelor degree of higher merit
  • profound knowledge in using Matlab
  • accurate, creative and independent working style
  • good written and oral communication skills
  • interest in scientific work

Conditions

Time frame: 6 months